Evolve Group
Machine Learning Engineer
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We are hiring a Senior AI/ML Engineer to join a quantitative trading team investing heavily in its next generation of machine learning capabilities.
This is a broad role spanning both machine learning engineering and model development. You will work closely with quantitative researchers and software engineers to improve how models are developed, trained, tested and deployed into production trading systems.
The team is expanding its use of deep learning and modern AI approaches across a range of trading strategies, creating significant scope to influence both the underlying ML infrastructure and the modelling stack.
What You’ll Work On
- Develop and improve machine learning and deep learning models used across quantitative research.
- Build scalable systems for training, evaluating and deploying models.
- Work with distributed CPU and GPU environments to support larger and more complex experiments.
- Improve research workflows, experimentation tooling and model reproducibility.
- Optimise model training and inference performance.
- Work alongside quantitative researchers on model architecture, experimentation and implementation.
- Help modernise the wider research and trading technology stack.
- Integrate ML models into performance-sensitive production systems.
- Explore the use of LLMs and agent-based approaches across research and engineering workflows.
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What We’re Looking For
- 5+ years of experience building sophisticated software or machine learning systems.
- Strong Python engineering skills, with C++ experience advantageous.
- Hands-on experience developing and working with machine learning models.
- Experience with frameworks such as PyTorch, JAX or TensorFlow.
- Experience with distributed training, GPU compute or large-scale ML workloads.
- Understanding of the full ML lifecycle, from experimentation and training through to production deployment.
- Strong software engineering fundamentals and experience building reliable production systems.
- Ability to work closely with researchers on technically complex and open-ended problems.
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The Opportunity
This is not a narrowly defined infrastructure role.
You will have exposure across both the engineering and modelling sides of machine learning, with the opportunity to shape how the team develops and applies ML across its research and trading strategies.
It would suit someone who enjoys building technically difficult systems but still wants to remain hands-on with models, experimentation and applied machine learning.
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